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Dynamic Error Bat Algorithm: Theory and Application to Magnetotelluric Inversion

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Názov: Dynamic Error Bat Algorithm: Theory and Application to Magnetotelluric Inversion
Autori: Shuai Qiao, Yue Yang, Zikun Zhou, Shiwen Li, Chuncheng Li, Xiaoping Liu, Xueqiu Wang
Zdroj: Minerals. 15:359
Informácie o vydavateľovi: MDPI AG, 2025.
Rok vydania: 2025
Popis: Metallic minerals and some nonmetallic deposits (such as gas hydrate and natural gas) exhibit significant resistivity contrast with their surrounding rocks. Therefore, magnetotelluric (MT) sounding, which is highly sensitive to low-resistivity anomalies, offers a unique advantage in identifying these mineral resources. For metallogenic systems in sedimentary environments with approximately layered structures, we propose the Dynamic Error Bat Algorithm (DEBA), which integrates the cooling strategy, the dynamized fit error function, and the Bat Algorithm. DEBA enhances the breadth of global exploration in the early iteration stages while focusing on the depth of local exploitation in the later stages, yielding a more effective fitting outcome and better identification of electrical interfaces. Validity and noise immunity tests on typical synthetic models prove the robustness of DEBA. For broadband MT stations from the central Songliao Basin, we observed that the model derived from three-dimensional inversion did not provide an ideal layering effect for the shallow structure. Notably, the apparent resistivity and phase curves of these MT stations are similar, suggesting that the shallow structure in the study area has approximately one-dimensional (1-D) features, a conclusion that was further supported by phase tensor analysis. To gain a clearer understanding of the shallow structure, we applied DEBA to perform an averaged 1-D inversion. The subsequent results reveal a low-resistivity layer, which may be attributed to metallic sulfides or saline fluids.
Druh dokumentu: Article
Jazyk: English
ISSN: 2075-163X
DOI: 10.3390/min15040359
Rights: CC BY
Prístupové číslo: edsair.doi...........9deb72016f26e8f6b7c4e9a8cf46d1dd
Databáza: OpenAIRE
Popis
Abstrakt:Metallic minerals and some nonmetallic deposits (such as gas hydrate and natural gas) exhibit significant resistivity contrast with their surrounding rocks. Therefore, magnetotelluric (MT) sounding, which is highly sensitive to low-resistivity anomalies, offers a unique advantage in identifying these mineral resources. For metallogenic systems in sedimentary environments with approximately layered structures, we propose the Dynamic Error Bat Algorithm (DEBA), which integrates the cooling strategy, the dynamized fit error function, and the Bat Algorithm. DEBA enhances the breadth of global exploration in the early iteration stages while focusing on the depth of local exploitation in the later stages, yielding a more effective fitting outcome and better identification of electrical interfaces. Validity and noise immunity tests on typical synthetic models prove the robustness of DEBA. For broadband MT stations from the central Songliao Basin, we observed that the model derived from three-dimensional inversion did not provide an ideal layering effect for the shallow structure. Notably, the apparent resistivity and phase curves of these MT stations are similar, suggesting that the shallow structure in the study area has approximately one-dimensional (1-D) features, a conclusion that was further supported by phase tensor analysis. To gain a clearer understanding of the shallow structure, we applied DEBA to perform an averaged 1-D inversion. The subsequent results reveal a low-resistivity layer, which may be attributed to metallic sulfides or saline fluids.
ISSN:2075163X
DOI:10.3390/min15040359